Ms. Meaad Alqahtany | Education | Research Excellence Award

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Ms. Meaad Alqahtany | Education | Research Excellence Award

Ms. Meaad Alqahtany, King Saud Bin Abdulaziz University for Health Sciences, Saudi Arabia

Meaad Alqahtany is a dedicated biologist specializing in cellular and molecular biology, with a focus on understanding the structural intricacies of prokaryotic cells. Currently a Research Assistant at King Saud bin Abdulaziz University for Health Sciences in Saudi Arabia, Meaad plays a key role in supporting research projects, monitoring ongoing studies, and contributing to data analysis. With prior experience as a part-time lecturer and science teacher, she brings a blend of academic rigor and practical teaching experience. Her research revolves around using high-resolution microscopies to investigate surface cell molecules, particularly in bacterial cells.

Professional Profile

Scopus

Summary of Suitability for the Research for Research Excellence Award

Meaad Alqahtany is a strong candidate for the Research for Research Excellence Award. Her extensive research experience, publication record, leadership initiatives, and passion for education make her well-suited for recognition. Her work in cellular and molecular biology, coupled with her ability to teach and mentor, positions her as a scientist contributing significantly to both her field and the broader scientific community.

๐ŸŽ“ Education

Meaad Alqahtany holds a Master of Science in Cell and Molecular Biology from the University of Arkansas (2019), where she researched bacterial cell proteins using advanced molecular techniques. She completed her Bachelorโ€™s in Biology (Microbiology) at King Abdulaziz University, Saudi Arabia, in 2014. In addition to her formal education, Meaad has also completed several advanced courses and workshops, including research data management, scientific writing, and statistical analysis. Her diverse educational background equips her with a deep understanding of biological sciences and the technical skills needed for cutting-edge research.

๐Ÿ’ผ Experience

Meaad has amassed significant experience across academic and research settings. As a Research Assistant since 2021, she has supported projects at King Saud bin Abdulaziz University for Health Sciences. Previously, she was a Lecturer at Bisha University, teaching Micro Techniques. From 2019-2021, she taught science to middle school students at Majestic International School, where she also organized science fairs. During her time at the University of Arkansas (2017-2019), she conducted advanced research on bacterial cell proteins as part of her graduate studies. Meaad has also been a Lab Instructor, training undergraduate students in biology lab techniques.

๐Ÿ…Awards and Honors

  • Founder and active member of the Biology Club at the College of Science
  • Organized New Students Orientation, Bio Day, and other student events
  • Led the 3-Minute Research Proposal competition at KSAU-HS
  • Presented research at international conferences on cellular biology
  • Received recognition for her contribution to scientific publications on antimicrobial mechanisms and nanoparticle effects

๐ŸŒ  Research Focus

Meaadโ€™s research focuses on cellular and molecular biology, particularly prokaryotic cells. She uses high-resolution microscopy techniques to investigate surface cell molecules, including histone-like proteins and nucleoid structuring in bacteria. Her studies aim to uncover the molecular mechanisms of how silver nanoparticles affect bacterial cells and their proteins, shedding light on antimicrobial actions. Meaad also delves into nanoparticle stability and its impact on biological systems, providing insight into how nanotechnology can influence microbiology.

 ๐Ÿ“– Publication Top Notes

  • Faculty and students perspectives towards game-based learning in health sciences higher education
  • Nanoscale reorganizations of histone-like nucleoid structuring proteins in Escherichia coli are caused by silver nanoparticles
    • Citations: 18

Dr. Roohollah Shirani Faradonbeh | Mining Engineering | Best Researcher Award

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Dr. Roohollah Shirani Faradonbeh | Mining Engineering | Best Researcher Award

Dr. Roohollah Shirani Faradonbeh, Curtin University, Australia

Dr. Roohollah Shirani Faradonbeh is an accomplished mining engineer with expertise in intelligent mining, mine electrification, and sustainable resource management. Currently, he serves as an Assistant Professor at Curtin Universityโ€™s WA School of Mines, where he contributes to innovative research in digital mining technologies and advanced rock mechanics. With a PhD in Mining Engineering from the University of Adelaide, his research focuses on AI-driven predictive models for rockburst risk assessment in underground mines. Dr. Shirani has published extensively on topics like mine tailings recovery, blasting optimization, and sustainable mining practices.

Professional profile

Google Scholar

Summary of Suitability for the โ€œResearch for Best Researcher Awardโ€ โ€“ Roohollah Shirani Faradonbeh

Dr. Roohollah Shirani Faradonbeh has an outstanding academic background and extensive experience in the field of mining engineering, making him a highly suitable candidate for the Research for Best Researcher Award. His research focuses on critical areas such as rockburst phenomena in deep underground mining, which has significant implications for safety and operations in the mining industry. His development of AI-based models and novel testing methodologies, as demonstrated in his doctoral work, has opened new frontiers in intelligent mining, especially in predicting and mitigating rockburst risks.

 ๐ŸŽ“Education

Dr. Shirani holds a PhD in Mining Engineering from the University of Adelaide, where his thesis explored AI-based models for predicting and controlling rockburst phenomena in deep underground mines. His MSc in Mining Engineering from Tarbiat Modares University focused on minimizing blast-induced ground vibrations using gene expression programming. During his BSc at the University of Kashan, he investigated methods for reducing the back-break phenomenon in Iranโ€™s Sungun Copper Mine. His educational journey highlights his expertise in predictive modeling, experimental mechanics, and sustainable mining practices.

 ๐Ÿ’ผ Experience

Dr. Shirani has held multiple academic and industry roles, including his current position as Assistant Professor at Curtin Universityโ€™s WA School of Mines. He has served as an industry advisor for Fortescue Metals Group and was a research and teaching assistant at the University of Adelaide. His teaching portfolio covers advanced topics like rock excavation technology, mine automation, and slope engineering. In addition to academic contributions, Dr. Shirani has supervised numerous PhD and M.Phil. students in fields such as autonomous mining systems, rockburst early warning tools, and environmental impact assessments for deep-sea mining.

 ๐Ÿ…Awards and Honors

Throughout his career, Dr. Shirani has received recognition for his contributions to mining engineering and research excellence. He has been honored with multiple academic awards for his innovative work in intelligent mining systems and AI-driven rockburst models. His research on blasting operations and ground vibration prediction has garnered attention from industry and academia alike. Additionally, Dr. Shirani has played a key role in international mining conferences, where his contributions to sustainable mining and resource recovery have been highly regarded by peers and industry professionals.

๐ŸŒ Research Focus

Dr. Shiraniโ€™s research centers on cutting-edge mining technologies, focusing on areas like mine digitalization, autonomous systems, and AI-based predictive models. He is particularly interested in the electrification and decarbonization of mining operations, as well as sustainable mine rehabilitation and waste management. His work in the experimental analysis of rockburst behavior and mine tailings recovery has paved the way for advancements in mining safety and efficiency. He also explores alternative mining methods, such as deep-sea mining and asteroid mining, reflecting his forward-thinking approach to resource extraction.

 ๐Ÿ“– Publications Top Notes

Forecasting blast-induced ground vibration developing a CART model
Cited by: 172
Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction
Cited by: 171
Prediction of the uniaxial compressive strength of sandstone using various modeling techniques
Cited by: 164
Combination of neural network and ant colony optimization algorithms for prediction and optimization of flyrock and back-break induced by blasting
Cited by: 153
Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques
Cited by: 147